It is common for communications receivers to extract a receive clock signal from the received data stream. Some communications protocols facilitate such Clock Data Recovery or CDR operation by constraining the communications signaling so as to distinguish between clock-related and data-related signal components. Similarly, some communications receivers process the received signals beyond the minimum necessary to detect data, so as to provide the additional information to facilitate clock recovery. As one example, a so-called double-baud-rate receive sampler may measure received signal levels at twice the expected data reception rate, to allow independent detection of the received signal level corresponding to the data component, and the chronologically offset received signal transition related to the signal clock component.
However, the introduction of extraneous communications protocol transitions is known to limit achievable data communication rate. Similarly, receive sampling at higher than transmitted data rate is known to substantially increase receiver power utilization.
Data-dependent receive equalization is also well known in the art. Generally, these time-domain-oriented equalization methods focus on compensating for the effects of inter-symbol-interference or ISI on the received signal. Such ISI is caused by the residual electrical effects of a previously transmitted signal persisting in the communications transmission medium, so as to affect the amplitude or timing of the current symbol interval. As one example, a transmission line medium having one or more impedance anomalies may introduce signal reflections. Thus, a transmitted signal will propagate over the medium and be partially reflected by one or more such anomalies, with such reflections appearing at the receiver at a later time in superposition with signals propagating directly.
One method of data-dependent receive equalization is Decision Feedback Equalization or DFE. Here, the time-domain oriented equalization is performed by maintaining a history of previously-received data values at the receiver, which are processed by a transmission line model to predict the expected influence that each of the historical data values would have on the present receive signal. Such a transmission line model may be precalculated, derived by measurement, or generated heuristically, and may encompass the effects of one or more than one previous data interval. The predicted influence of these one or more previous data intervals is collectively called the DFE compensation. At low to moderate data rates, the DFE compensation may be calculated in time to be applied before the next data sample is detected, as example by being explicitly subtracted from the received data signal prior to receive sampling, or implicitly subtracted by modifying the reference level to which the received data signal is compared in the receive data sampler or comparator. However, at higher data rates the detection of previous data bits and computation of the DFE compensation may not be complete in time for the next data sample, requiring use of so-called “unrolled” DFE computations performed on speculative or potential data values rather than known previous data values. As one example, an unrolled DFE stage may predict two different compensation values depending on whether the determining data bit will resolve to a one or a zero, with the receive detector performing sampling or slicing operations based on each of those predictions, the multiple results being maintained until the DFE decision is resolved.